The Effect of International Traffic Stagnation on Malaria Cases in Japan

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Abstract

Background: Aiming to identify the potentially reduced malaria cases by international traffic stagnation after pandemic of COVID-19, the association of entries for Japanese and foreigners with malaria cases during past two decades in Japan was examined.Methods: A longitudinal analysis of malaria cases as well as entries for Japanese and foreigners was conducted using data from April 5th, 1999 to September 30th, 2021 in Japan. Generalized regression model was used to examine an association of time trend with entries for Japanese and foreigners using data from April 1999 to December 2019, to estimate the potentially reduced number of entries after 2020. Multivariable risk ratios were calculated with Poison regression model as predictive model of malaria cases by the number of entries for Japanese and foreigners. The potentially reduced number of malaria cases was estimated by the potentially reduced number of entries for Japanese and foreigners after 2020 using multivariable Poison regression model.Findings: A total of 1,534 malaria cases was identified between April 5th, 1999 and September 30 th, 2021. The multivariable risk ratio (95% confidence intervals) of malaria case numbers per 100,000 persons increment of entries was 3.51(1.54-7.99) for Japanese and 1.44(0.91-2.30) for foreigners in the model including both of the number of entries for Japanese and that for foreigners. During 2020, a total of 28(95% confidence limits: 22-34) malaria cases was estimated to be potentially reduced, which accounted for 58%(53%-63%) of malaria cases in Japan.Interpretation: These finding suggest that international traffic stagnation after pandemic of COVID-19 reduced the number of malaria cases in Japan.. Funding Information: No funding source was used for this study.Declaration of Interests: The author declares no competing interests.Ethics Approval Statement: Informed consent is not needed in this study, because publicly available data was used from website and former published reports.

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